The Rise of AI Agent Economy: Virtuals Protocol Leads the Trillion-Dollar Market

Recently, the development of AI technology has entered a new stage. The performance gap among mainstream large language models is gradually narrowing, and the industry's focus is shifting from technological development to practical applications. Against this backdrop, AI agents have become a new hotspot.

AI agents are different from traditional passive AI tools; they are more like proactive systems that can fully understand tasks and make autonomous judgments. For example, when booking a restaurant, AI agents can not only recommend restaurants but also take into account user preferences, search for popular options, and even assist with real-time reservations.

However, individual AI agents also have limitations. They cannot become experts in all fields and are constrained by memory and computational capacity. Therefore, collaboration between AI agents with different specializations becomes crucial. However, achieving this collaboration is not easy and requires addressing a series of issues such as scope of work, quality standards, pricing, and delivery evaluation.

To address these challenges, the Virtuals protocol proposes the Agent Commerce Protocol (ACP). ACP aims to standardize the trading methods between agents, enabling agents from different platforms to collaborate smoothly. It consists of four main phases: request, negotiation, transaction, and evaluation, similar to the process of traditional companies issuing requests for proposals, but automated through smart contracts.

Through ACP, AI agents can operate as independent economic entities 24/7 without interruption. This creates possibilities for entirely new business models. For example, on-chain hedge funds can be collaboratively managed by multiple specialized AI agents to perform tasks such as market analysis, risk management, and portfolio optimization. Similarly, in the field of media production, AI agents can independently complete the entire process from content planning to production and distribution.

Currently, there are about 1 million public agents operating on-chain, generating approximately $1 billion in Gross Agent Product (GAP) annually. It is expected that this scale could grow to $1 trillion by 2035. However, achieving this growth still faces challenges, particularly in terms of privacy protection. With the development of technologies such as zero-knowledge proofs, these limitations are expected to be gradually overcome.

The AI agent economy has transformed from imagination into reality, demonstrating enormous development potential. With continuous advancements and improvements in technology, we have reason to expect that AI agents will play an increasingly important role in future economic development.